Abstract
A Histogram Analysis in Radiation Therapy (HART) program was primarily developed to increase the efficiency and accuracy of dose–volume histogram (DVH) analysis of large quantities of patient data in radiation therapy research. The program was written in MATLAB to analyze patient plans exported from the treatment planning system (Pinnacle3) in the American Association of Physicists in Medicine/Radiation Therapy Oncology Group (AAPM/RTOG) format. HART‐computed DVH data was validated against manually extracted data from the planning system for five head and neck cancer patients treated with the intensity‐modulated radiation therapy (IMRT) technique. HART calculated over 4000 parameters from the differential DVH (dDVH) curves for each patient in approximately 10–15 minutes. Manual extraction of this amount of data required 5 to 6 hours. The normalized root mean square deviation (NRMSD) for the HART–extracted DVH outcomes was less than 1%, or within 0.5% distance‐to‐agreement (DTA). This tool is supported with various user‐friendly options and graphical displays. Additional features include optimal polynomial modeling of DVH curves for organs, treatment plan indices (TPI) evaluation, plan‐specific outcome analysis (POA), and spatial DVH (zDVH) and dose surface histogram (DSH) analyses, respectively. HART is freely available to the radiation oncology community.PACS numbers: 87.53.‐j; 87.53.Tf; 87.53.Xd.
Highlights
138 Pyakuryal et al: An efficient dose–volume histogram (DVH) analysis tool pancreas, liver, and prostate cancers has been well reported in the literature.[1,2,3,4,5] The sensitivity of tumor control probabilities (TCP) and normal tissue complication probabilities (NTCP) calculations to small changes in the DVH shape points requires an accurate and efficient method of computing DVH parameters.[6]A DVH represents a frequency distribution of average dose values over a 3D matrix of voxels composed of planning target volumes (PTVs) or critical structures within the patient anatomy.[6]
This paper describes the development of the software (HART) and assesses its performance by comparing the results with manually extracted data from a commercial treatment planning system (TPS)
Features such as optimal polynomial fittings of cDVH curves for organs, treatment plan indices (TPI) evaluation techniques, and plan-specific outcome analysis (POA) options have been incorporated into Histogram Analysis in Radiation Therapy (HART)
Summary
138 Pyakuryal et al: An efficient DVH analysis tool pancreas, liver, and prostate cancers has been well reported in the literature.[1,2,3,4,5] The sensitivity of TCP and NTCP calculations to small changes in the DVH shape points requires an accurate and efficient method of computing DVH parameters.[6]A DVH represents a frequency distribution of average dose values over a 3D matrix of voxels composed of planning target volumes (PTVs) or critical structures within the patient anatomy.[6]. The cDVH data points requested for clinical studies can be manually extracted from the commercial treatment planning system (TPS). This is reasonable for a limited number of structures and DVH data points, the manual method is prone to errors and is time-consuming when analyzing a large number of structures, patients and cDVH points of interest. It was originally designed to expedite the extraction and analysis of DVH data from a swallowing physiology study involving 150 to 200 head and neck cancer patients treated with IMRT. Manual extraction of all the DVH data points of interest directly from the TPS was very time-consuming and prone to error. Scripting within the planning system could achieve the similar extraction results but would not provide the same flexibility and functionality for DVH analysis
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